Talk by William Softky and Criscillia Benford (bio's below), given to the Redwood Center for Theoretical Neuroscience at UC Berkeley.
Medical and governmental authorities around the world have identified a host of problematic behaviors with names like internet addiction, gaming addiction, and texting addiction; most of us know sufferers. The scale of these technology-related addictions is vast, and their social impacts profound, but because the behaviors themselves are so different, they have been investigated separately. We propose that they are unified by their common informational delivery medium: screens. If one views humans not as consumers of “content” but as sophisticated signal-processing engines evolved to self-calibrate in a natural environment, then information theory becomes a tool to illuminate not only our informational urges, but the ways in which those urges respond to various sources. In that statistical language, screens are distinctly un-natural. Natural signal sources are continuous and three-dimensional, with coherence and salience rare. Screens, on the other hand, present signals quantized in space (pixels) and time (frames), arranged on a 2-D sheet, and enhanced for both coherence and salience, features which combine to form a source both topologically and entropically utterly unlike Nature, and thus likely to de-calibrate sensory processing. Furthermore, we propose that the de-calibrating influence of screens accelerates into the vicious circle of addictive behavior because the input from screens in fact feeds elemental informational urges. Our native love of lower-entropy inputs like saturated colors, clear images, pure tones, and sharp contours originally evolved to help us re-calibrate in confusing high-entropy environments, where such sources were rare and could not be over-indulged. In that case a nervous system could remain in homeostatic equilibrium by alternating between the difficult signal-processing tasks it must pursue (like foraging) and the easy, unambiguous tasks it enjoys and uses for data validation. Unfortunately, if the calibration problem already results from oversimplified input (like from screens), feeding it with more of the same only makes the problem worse. Our brains’ informational needs are more basic than any given source or sensory modality; only when we understand those needs can we respect and fulfill them.
==== Bio’s ============
While a graduate student at Caltech’s Computation and Neural Systems Program (under Christof Koch), Bill Softky evangelized a high-bandwidth neocortical code based on precise spike timing ( >2000 citations on Google Scholar). After a post-doc at NIH’s Math Research Branch, Bill worked in Silicon Valley at a variety of startup technology companies, beginning as Senior Engineer and most recently as Chief Algorithm Officer of two acquired companies, Demdex and TapCommerce. He applied his theoretical understanding of neuroscience principles to real-time business operating systems, and his practical understanding of business algorithms to brains as a Principle Investigator first at the Redwood Neuroscience Institute, and lately as an independent consultant.
Criscillia Benford is a specialist in narrative theory and nineteenth-century English literature and culture who has held teaching positions at The University of Chicago, Duke, and Stanford. She currently teaches nineteenth-century English literature in the Stanford Continuing Studies Program. Her most recent publication, a co-edited 150th anniversary edition of George Meredith’s Modern Love and Poems of the English Roadside, with Poems and Ballads for Yale University Press, was selected by Choice as an “Outstanding Academic Title” for 2013. She expects to complete her monograph examining multiplot narratives through the lenses of narrative theory and information theory by the end of this year. She received her PhD in English and American literature from Stanford.